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The term “big data” describes huge complex volumes of ever-increasing information processed through digital technologies for use in several fields of endeavor. The rapid rise of Internet technology in the 21st century has brought the ability to generate, store, and analyze enormous volumes of data within a short period.
There are over 35 billion devices connected to the Internet today, with that figure expected to rise to over 75 billion by 2025. Big data is the system for analyzing and converting this vast cache of data to useful information that can affect the world. The primary use of big data is to help corporations make more accurate business decisions.
Experts describe big data characteristics using the five Vs:
Volume talks about how much data is generated. The quantity of data available is enormous and continues to increase rapidly.
Big data users have to utilize incoming data quickly, in real-time, if possible. The speed of data utilization helps companies make precise decisions, providing a competitive advantage.
Big data comes in various forms. It could be structured, semi-structured, or unstructured and include facts, statistics, texts, photos, and videos.
The quality and accuracy of received data are important. Inaccurate or inconsistent information will affect the value the data provides.
Value measures the usefulness of received data, what it can achieve, and how companies can use it to transform their services.
Big data has found use in government, banking and finance, technology, fraud detection, social media analytics, agriculture, call center analytics, marketing, telecommunications, and healthcare.
The medical sector appears to be behind others in the adoption and application of big data, mainly due to resistance from healthcare providers. Experts in the industry would rather make treatment decisions based on their experience and skills rather than insights from big data. However, access to new information is beginning to see big data gain a foothold in the healthcare industry. Advances in medical technology are also improving the ability of healthcare personnel to interact with and utilize big data.
Healthcare services before the introduction of big data analytics required minimal patient information. Hospitals would only obtain basic patient details, like name, age, medical history, and disease condition. This data fails to provide in-depth perspectives into health conditions and can limit the treatment course of action. Big data’s holistic approach to information gathering improves disease understanding and helps doctors to provide more accurate, individualized treatment.
Big data aggregates information from multiple scales providing panoramic views on disease causes leading to more accurate diagnoses. Data from cells, tissues, organs, organisms, DNA, proteins, metabolites, and ecosystems have broadened the scope of disease research. By integrating information from multiple sources, big data can help understand the biology of diseases in individuals.
The data from multiple sources also enhances disease prediction methods. Suppose a patient had a heart attack, for example, data on when the incident happened, stressful events leading to the attack, and the patient’s lifestyle could help doctors provide insight on preventing future attacks.
Data from multiple sources is helpful in determining disease prevalence and treatment efficacy. StuffThatWorks, a crowdsourcing platform, uses AI-generated data to assess the effectiveness of treatment options for a wide range of ailments. The generated data informs and helps patients find alternative treatment options for their conditions.
Smart wearable devices help doctors to obtain vital patient information even when they are away from the hospital. Doctors can monitor heart rate, sleep habits, glucose levels, etc., constantly, providing a means of identifying potential health conditions. A person who is having trouble sleeping, for instance, could be at risk of heart disease, and doctors can begin to advise them on preventing measures. Wearable devices also allow patients to be actively involved in monitoring their health.
Patients who are away from the hospitals may develop symptoms needing emergency intervention. Doctors can also use wearables to attend to emergencies without bringing patients to the hospital, saving hospital costs on in-house treatment.
Big data provides patient admission trends and forecasts in hospitals, helping management employ and schedule the right number of staff for their operations. Overstaffing can increase labor and overhead costs while understaffing can lead to poor service, which can be detrimental to patients’ health. Big data utilizes past admission records to find patterns in admission rates, accurately predicting patient load and scheduling staff accordingly.
The healthcare industry is one of the worst affected industries when it comes to cyber breaches. This is because personal medical data commands a small fortune on the dark web, and to prevent these attacks, medical organizations are turning to big data. Big data uses network traffic changes and other security markers to identify potential security breaches. There are valid concerns about the security vulnerabilities of big data, but improving security systems, data encryption, and firewalls enhance the reliability of big data as a security measure.
Big data also protects healthcare organizations from inaccurate claims and fraud by structuring the claims and payment processing, so genuine claimants get better returns on their claims and staff get paid on time.
Big data is in its nascent stages, and there are many rough edges to smoothen. Organizations are trying to keep up with the rapid growth and changing technology. The vast sea of data often means that people struggle to know what it all means. The administration of big data in terms of information management and implementation is also concerning. Finally, not enough healthcare organizations possess systems and databases to handle the mass inflow of data.
Big data is still a new concept in the modern world, but there is no disputing its potential to revolutionize healthcare and health services provision. Bringing big data into the mainstream healthcare sector represents a massive shift, and many in the industry are understandably skeptical. But as the benefits and potentials become more apparent, there is little doubt that the vast majority of people in the medical world will embrace big data.